class_docstr: *MUSAN* :cite:`musan2015` dataset.
  
  Args:
      root (str or Path): Root directory where the dataset's top-level directory exists.
      subset (str): Subset of the dataset to use. Options: [``"music"``, ``"noise"``, ``"speech"``].
docstr: Return the n-th sample in the dataset.
  
  Args:
      n (int): Index of sample to be loaded.
  
  Returns:
      (torch.Tensor, int, str):
          torch.Tensor
              Waveform.
          int
              Sample rate.
          str
              File name.
docstr_tok: ["Return","the","n-th","sample","in","the","dataset",".","Args",":","n","(","int",")",":","Index","of","sample","to","be","loaded",".","Returns",":","(","torch.Tensor",",","int",",","str",")",":","torch.Tensor","Waveform",".","int","Sample","rate",".","str","File","name","."]
code: def __getitem__(self, n: int) -> Tuple[torch.Tensor, int, str]:
      r"""Return the n-th sample in the dataset.
  
      Args:
          n (int): Index of sample to be loaded.
  
      Returns:
          (torch.Tensor, int, str):
              torch.Tensor
                  Waveform.
              int
                  Sample rate.
              str
                  File name.
      """
      audio_path, sample_rate, filename = self.get_metadata(n)
      path = Path(audio_path)
      return (
          _load_waveform(path.parent, path.name, sample_rate),
          sample_rate,
          filename,
      )
  
file_path: audio/src/torchaudio/prototype/datasets/musan.py
imports: from pathlib import Path
  from typing import Tuple, Union
  import torch
  from torch.utils.data import Dataset
  from torchaudio.datasets.utils import _load_waveform
label_desc: Use image node_id 3 for calling the Musan obj's underlying member method code with example usage: obj.__getitem__(n) and returns: _load_waveform,  sample_rate,  filename